Interactive online learning for clinical entity recognition
Abstract
References
Index Terms
- Interactive online learning for clinical entity recognition
Recommendations
Entity recognition from colloquial text
AbstractExtraction of concepts and entities of interest from non-formal texts such as social media posts and informal communication is an important capability for decision support systems in many domains, including healthcare, customer relationship ...
Highlights- This research focuses on the healthcare domain and investigates the problem of symptom recognition from colloquial texts.
- We designed and evaluated several training strategies for seven BERT-based entity recognition models.
- Tested ...
KG-ZESHEL: Knowledge Graph-Enhanced Zero-Shot Entity Linking
K-CAP '21: Proceedings of the 11th Knowledge Capture ConferenceEntity linking is a fundamental task for a successful use of knowledge graphs in many information systems. It maps textual mentions to their corresponding entities in a given knowledge graph. However, with the rapid evolution of knowledge graphs, a ...
Improving Entity Linking by Encoding Type Information into Entity Embeddings
Chinese Computational LinguisticsAbstractEntity Linking (EL) refers to the task of linking entity mentions in the text to the correct entities in the Knowledge Base (KB) in which entity embeddings play a vital and challenging role because of the subtle differences between entities. ...
Comments
Information & Contributors
Information
Published In
Sponsors
- Paxata: Paxata
- tableau: Tableau Software
- Trifacta: Trifacta
- IBM: IBM
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
Conference
- Paxata
- tableau
- Trifacta
- IBM
Acceptance Rates
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 220Total Downloads
- Downloads (Last 12 months)12
- Downloads (Last 6 weeks)2
Other Metrics
Citations
Cited By
View allView Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in